K. Hoebel

发表

Balloon catheter-based radiofrequency ablation monitoring in porcine esophagus using optical coherence tomography.

N. Nishioka, N. Uribe-Patarroyo, B. Vakoc, 2019, Biomedical optics express.

Fair Conformal Predictors for Applications in Medical Imaging

Jayashree Kalpathy-Cramer, Ken Chang, K. Hoebel, 2021, AAAI.

Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging

James M. Brown, Matthew D. Li, Deniz Erdoğmuş, 2020, npj Digital Medicine.

Federated Learning for Breast Density Classification: A Real-World Implementation pdf

Daguang Xu, Jesse Tetreault, Ahmed Harouni, 2020, DART/DCL@MICCAI.

Do I know this? segmentation uncertainty under domain shift

Jayashree Kalpathy-Cramer, Ken Chang, J. Patel, 2022, Medical Imaging.

Is this good enough? On expert perception of brain tumor segmentation quality

Jayashree Kalpathy-Cramer, T. Batchelor, E. Gerstner, 2022, Medical Imaging.

Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging.

James M. Brown, Matthew D. Li, Deniz Erdoğmuş, 2020, NPJ digital medicine.

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results

Bjoern H Menze, Minh H. Vu, Nisarg A. Shah, 2021, The journal of machine learning for biomedical imaging.

Radiomics Repeatability Pitfalls in a Scan-Rescan MRI Study of Glioblastoma.

James M. Brown, Andrew L Beers, Praveer Singh, 2021, Radiology. Artificial intelligence.

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results pdf

Christos Davatzikos, Gowtham Krishnan Murugesan, Chandan Ganesh, 2021, ArXiv.

Segmentation, Survival Prediction, and Uncertainty Estimation of Gliomas from Multimodal 3D MRI Using Selective Kernel Networks

Praveer Singh, B. Rosen, Jayashree Kalpathy-Cramer, 2020, BrainLes@MICCAI.

Deep Learning Vessel Segmentation for Microsurgical Free Tissue Transfer

Ken Chang, Jayashree Kalpathy-Cramer, Katharina Hoebel, 2019 .

Monte Carlo dropout increases model repeatability pdf

Jayashree Kalpathy-Cramer, Christopher P. Bridge, Katharina Hoebel, 2021, ArXiv.

Inconsistent Partitioning and Unproductive Feature Associations Yield Idealized Radiomic Models.

Praveer Singh, Jayashree Kalpathy-Cramer, C. Fuller, 2022, Radiology.

Improving the repeatability of deep learning models with Monte Carlo dropout

Jayashree Kalpathy-Cramer, A. Rodriguez, M. Schiffman, 2022, npj Digital Medicine.

DeepNeuro: an open-source deep learning toolbox for neuroimaging

Bruce R. Rosen, James M. Brown, Ken Chang, 2018, Neuroinformatics.

Federated Learning for Breast Density Classification: A Real-World Implementation

Colin B. Compas, Richard D. White, Mona G. Flores, 2020, DART/DCL@MICCAI.

Evaluating subgroup disparity using epistemic uncertainty in mammography pdf

Jayashree Kalpathy-Cramer, Katharina Hoebel, Andreanne Lemay, 2021, ArXiv.

Assessing the validity of saliency maps for abnormality localization in medical imaging pdf

Ken Chang, Jayashree Kalpathy-Cramer, Mishka Gidwani, 2020, ArXiv.

Multi-Institutional Assessment and Crowdsourcing Evaluation of Deep Learning for Automated Classification of Breast Density.

Ken Chang, Jayashree Kalpathy-Cramer, Laura Brink, 2020, Journal of the American College of Radiology : JACR.

An exploration of uncertainty information for segmentation quality assessment

Vincent Andrearczyk, Ken Chang, Jayashree Kalpathy-Cramer, 2020, Medical Imaging: Image Processing.

Addressing catastrophic forgetting for medical domain expansion pdf

Daniel L. Rubin, Jayashree Kalpathy-Cramer, Mishka Gidwani, 2021, ArXiv.

Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging

James M. Brown, Matthew D. Li, Deniz Erdoğmuş, 2020, npj Digital Medicine.

Machine learning models can detect aneurysm rupture and identify clinical features associated with rupture.

Andrew L Beers, Jayashree Kalpathy-Cramer, Ken Chang, 2019, World neurosurgery.

The unreasonable effectiveness of Batch-Norm statistics in addressing catastrophic forgetting across medical institutions pdf

Jayashree Kalpathy-Cramer, Daniel L Rubin, Mishka Gidwani, 2020, ArXiv.

FDU-Net: Deep Learning-Based Three-Dimensional Diffuse Optical Image Reconstruction

Jayashree Kalpathy-Cramer, S. Carp, J. Patel, 2023, IEEE Transactions on Medical Imaging.

Structural and functional vascular dysfunction within brain metastases is linked to pembrolizumab inefficacy

Praveer Singh, A. Giobbie-Hurder, Jayashree Kalpathy-Cramer, 2023, bioRxiv.

Assessing the Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical Imaging.

Matthew D. Li, Praveer Singh, Jayashree Kalpathy-Cramer, 2021, Radiology. Artificial intelligence.

Not without Context-A Multiple Methods Study on Evaluation and Correction of Automated Brain Tumor Segmentations by Experts.

Jayashree Kalpathy-Cramer, K. Hoebel, Saivenkat H Vagvala, 2023, Academic radiology.

A Deep Learning Based Framework for Joint Image Registration and Segmentation of Brain Metastases on Magnetic Resonance Imaging

Praveer Singh, Jayashree Kalpathy-Cramer, P. Brastianos, 2023, MLHC.